Evidence map›Paper›PMID 41422013›Full record

ArticleVirology journal2025

Integrative single-cell transcriptomic analysis reveals immunomodulatory hub genes and candidate compounds for HIV-associated chronic inflammation.

Md Imran Hasan, Srinivas Mummidi, Ashley I Teufel

Abstract read
In one paragraph

Article in Virology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Md Imran HasanDepartment of Natural Sciences, College of Arts and Sciences, Texas A&M University-San Antonio, TX, USA.
Srinivas MummidiDepartment of Health and Behavioral Sciences, College of Arts and Sciences, Texas A&M University-San Antonio, TX, USA.
Ashley I TeufelDepartment of Natural Sciences, College of Arts and Sciences, Texas A&M University-San Antonio, TX, USA. ateufel@tamusa.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite significant advances in treatment and prevention, HIV remains a major global health challenge affecting millions worldwide. In this study, we developed a pipeline combining single-cell RNA sequencing (scRNA-seq) analysis with molecular modeling to identify potential biomarkers and therapeutic targets in HIV infection. Analysis of scRNA-seq data from individuals with HIV revealed 69 differentially expressed genes. Protein-protein interaction network analysis identified five hub genes (STAT1, ISG15, MX1, BCL2, and TNFSF10). Regulatory network analysis identified transcription factors and microRNAs governing the expression of these hub genes. Molecular docking simulations identified Dolutegravir and Luteolin as compounds capable of binding to STAT1, ISG15, and MX1, with favorable ADMET profiles. These compounds may potentially modulate chronic inflammation associated with persistent interferon signaling in HIV infection. Our study demonstrates an integrative approach to scRNA-seq data analysis, transforming transcriptomic data into actionable insights by identifying specific gene targets and potential candidate compounds that could inform the design of targeted experimental studies.

Indexed as

HIV InfectionsInflammationSingle-Cell AnalysisTranscriptomeGene Expression ProfilingGene Regulatory NetworksHeterocyclic Compounds, 3-RingHumansLuteolinMicroRNAsMolecular Docking SimulationPiperazinesProtein Interaction MapsPyridonesHeterocyclic Compounds, 3-RingLuteolinMicroRNAsPiperazinesPyridonesHIVMolecular dockingNetwork Analysis

Identifiers

PMID41422013
PMCPMC12838008

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.